The productivity change of a decision making unit (DMU) between two time periods can be evaluated by the Malmquist productivity index. In this study, we propose a method to compute the Malmquist productivity index in several time periods (from the first to the last periods) on interval data in data envelopment analysis (DEA). Then, the obtained Malmquist productivity index is compared with Malm...

Data envelopment analysis (DEA) is a method for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. In this paper, we study the measurement of DMU performances in DEA in situations where input and/or output values are given as imprecise data. By imprecise data we mean situations where we only know that the actual val...

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

This study designs optimal systems for the centralized structures in data envelopmentanalysis (DEA). It assumes that a collection of decision making units (DMUs) with a masterdecision maker and a certain budget for them is available and introduces an optimal systemfor each DMU by maximizing their total revenue. A nmerical example is used to illustrate theproposed model.

  For efficiency evaluation of some of the Decision Making Units that have uncertain information, Rough Data Envelopment Analysis technique is used, which is derived from rough set theorem and Data Envelopment Analysis (DEA). In some situations rough data alter nonradially. To this end, this paper proposes additive rough–DEA model and illustrates the proposed model by a numerical example.

traditional dea models deal with measurements of relative eciency ofdmus regarding multiple - inputs vs. multiple-outputs. one of the drawbacksof these model is the neglect of intermediate products or linkong activities. af-ter pointing out needs for inclusion of them to dea models. we propose hybridmodel that can deal with intermediate products formally using this model wecan evaluate divisio...

Efficiency and evaluation is one of the main and most important demands of organizations, companies and institutions. As these organizations deal with a large amount of data, therefore, it is necessary to evaluate them on the basis of scientific methods to improve their efficiency. Data envelopment analysis is a suitable method for measuring the efficiency and performance of organizations. This...

Data Envelopment Analysis )DEA( is a technique for measuring the efficiency of decision making units. In all models of the DEA, for each unit under assessment, the numerical efficiency which may be less than or equal to one is obtained. Given the possible large number of efficiency units for evaluating units, we use various methods of ranking. span style="font-family: Cambria Math;font-size:8pt...

This study examines the productivity changes of decision making units in situation whereinput price vectors are varying between them and inputs are heterogeneous; that is a noncompetitivemarket. We present a directional measure of cost Malmquist productivity indexwhere incorporates the decision maker's preference over productivity change over time. Asimple numerical example is designed to illus...

There are situations that Decision Making Units (DMU’s) have uncertain information and their inputs and outputs cannot alter redially. To this end, this paper combines the rough set theorem (RST) and Data Envelopment Analysis (DEA) and proposes a non-redial Rough-DEA (RDEA) model so called additive rough-DEA model and illustrates the proposed model by a numerical example.